Masoud Mohseni

Artificial Intelligence · 2007–2022

A researcher in the Science corpus: 17 papers; trusts 7 researchers and is trusted by 31 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 280 citations into it; #7,084 of 35,345 by trust here, #2,388 by citations
• Atomic and Molecular Physics, and Optics — 185 citations into it; #1,041 of 7,135 by trust here, #383 by citations
• Computational Theory and Mathematics — 58 citations into it
• Electrical and Electronic Engineering — 26 citations into it
• Optimization & Training — 10 citations into it
• Statistical and Nonlinear Physics — 10 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it
• Management Science and Operations Research — 5 citations into it

Whom Masoud Mohseni trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Yazhen Wang
2. Kevin P. Murphy
3. Iroon Polytechniou
4. Isaac L. Chuang
5. David John Cameron MacKay
6. Diederik P. Kingma
7. Ethem Alpaydin
8. Radford M. Neal
9. H. Breuer
10. Yoshua Bengio

Who trusts Masoud Mohseni overall

1. Maria Schuld
2. Seogjoo J. Jang
3. Vedran Dunjko
4. Seth Lloyd
5. Roman Orus
6. M. Cerezo
7. S. Nawaz
8. Iordanis Kerenidis
9. Benedetta Mennucci
10. Guang Hao Low

Papers from Masoud Mohseni's perspective

Ordered by how strongly the researchers Masoud Mohseni trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. Going deeper with convolutions
9. ImageNet: A large-scale hierarchical image database
10. Deep Learning

Their papers

• Environment-assisted quantum walks in photosynthetic energy transfer. (2008) — 1,062 citations
• Quantum approximate optimization of non-planar graph problems on a planar superconducting processor (2020) — 622 citations
• Layerwise learning for quantum neural networks (2020) — 355 citations
• Suppressing quantum errors by scaling a surface code logical qubit (2022) — 1,354 citations
• Exponential suppression of bit or phase errors with cyclic error correction (2021) — 443 citations
• Quantum advantage in learning from experiments (2021) — 690 citations
• Hartree-Fock on a superconducting qubit quantum computer (2020) — 849 citations
• Power of data in quantum machine learning (2020) — 1,021 citations
• Observation of separated dynamics of charge and spin in the Fermi-Hubbard model (2020) — 165 citations
• Quantum supremacy using a programmable superconducting processor (2019) — 7,893 citations
• Quantum algorithms for supervised and unsupervised machine learning (2013) — 897 citations
• Quantum support vector machine for big feature and big data classification (2013) — 683 citations
• Quantum principal component analysis (2013) — 799 citations
• Towards quantum chemistry on a quantum computer. (2009) — 773 citations
• Environment-assisted quantum transport (2008) — 758 citations
• Polynomial-time quantum algorithm for the simulation of chemical dynamics (2008) — 379 citations
• Quantum Process Tomography: Resource Analysis of Different Strategies (2007) — 399 citations